Bump named-arrays to 0.14.2

docs/index.rst

@@ -61,7 +61,7 @@ and display as a false-color movie.
 
     # Take the mean of the wavelength over the spatial
     # and temporal axes since it is constant
-    wavelength = obs.inputs.wavelength.mean(axis_txy)
+    wavelength = obs.inputs.wavelength.mean(obs.axis_time)
 
     # Convert to Doppler velocity
     velocity = wavelength.to(
@@ -92,9 +92,6 @@ and display as a false-color movie.
         wavelength_max=velocity_max,
     )
 
-    # Isolate the angular position of each RGB point
-    position = obs.inputs.position.mean(obs.axis_wavelength)
-
     # Display the result as an RGB movie
     with astropy.visualization.quantity_support():
         fig, ax = plt.subplots(
@@ -105,8 +102,8 @@ and display as a false-color movie.
         )
         ani = na.plt.pcolormovie(
             obs.inputs.time,
-            position.x,
-            position.y,
+            obs.inputs.position.x,
+            obs.inputs.position.y,
             C=rgb,
             axis_time=obs.axis_time,
             axis_rgb=obs.axis_wavelength,
@@ -131,6 +128,14 @@ and display as a false-color movie.
     IPython.display.HTML(ani.to_jshtml())
 
 
+References
+==========
+
+.. bibliography::
+
+|
+
+
 Indices and tables
 ==================
 

iris/sg/_spectrograph.py

@@ -57,7 +57,7 @@ class SpectrographObservation(
         # red/green/blue channels
         rgb, colorbar = na.colorsynth.rgb_and_colorbar(
             spd=obs.outputs,
-            wavelength=obs.inputs.wavelength.mean(("detector_x", "detector_y")),
+            wavelength=obs.inputs.wavelength.mean(obs.axis_time),
             axis=obs.axis_wavelength,
             spd_min=0 * u.DN,
             spd_max=np.nanpercentile(
@@ -70,9 +70,6 @@ class SpectrographObservation(
             wavelength_max=wavelength_max,
         )
 
-        # Isolate the angular position of each RGB point
-        position = obs.inputs.position.mean(obs.axis_wavelength)
-
         # Isolate the first raster of the observation
         index = {obs.axis_time: 0}
 
@@ -85,7 +82,7 @@ class SpectrographObservation(
                 constrained_layout=True,
             )
             na.plt.pcolormesh(
-                position[index],
+                obs.inputs.position[index],
                 C=rgb[index],
                 axis_rgb=obs.axis_wavelength,
                 ax=ax[0],

iris/sg/background/_background.py

@@ -73,10 +73,11 @@ def average(
             )
     """
     obs = obs.copy_shallow()
+    shape = obs.shape
     obs.inputs = na.TemporalSpectralPositionalVectorArray(
         time=obs.inputs.time.ndarray.jd.mean(),
-        wavelength=obs.inputs.wavelength.mean(axis),
-        position=obs.inputs.position.mean(axis),
+        wavelength=obs.inputs.wavelength.broadcast_to(shape).mean(axis),
+        position=obs.inputs.position.broadcast_to(shape).mean(axis),
     )
     obs.outputs = np.nanmedian(obs.outputs, axis=axis)
     return obs
@@ -740,17 +741,17 @@ def estimate(
             )
             ax[0].set_title("original")
             na.plt.pcolormesh(
-                obs.inputs.position.x[index].mean(obs.axis_wavelength),
-                obs.inputs.position.y[index].mean(obs.axis_wavelength),
+                obs.inputs.position.x[index],
+                obs.inputs.position.y[index],
                 C=np.nanmean(obs.outputs.value[index], axis=obs.axis_wavelength),
                 ax=ax[0],
                 norm=mappable.norm,
                 cmap=mappable.cmap,
             )
             ax[1].set_title("corrected")
             na.plt.pcolormesh(
-                obs_nobg.inputs.position.x[index].mean(obs.axis_wavelength),
-                obs_nobg.inputs.position.y[index].mean(obs.axis_wavelength),
+                obs_nobg.inputs.position.x[index],
+                obs_nobg.inputs.position.y[index],
                 C=np.nanmean(obs_nobg.outputs.value[index], axis=obs.axis_wavelength),
                 ax=ax[1],
                 norm=mappable.norm,
@@ -781,12 +782,12 @@ def estimate(
         with astropy.visualization.quantity_support():
             fig, ax = plt.subplots()
             na.plt.plot(
-                obs.inputs.wavelength.mean(axis=axis_txy),
+                obs.inputs.wavelength.mean(obs.axis_time),
                 np.nanmedian(obs.outputs, axis=axis_txy),
                 label="original",
             )
             na.plt.plot(
-                obs_nobg.inputs.wavelength.mean(axis=axis_txy),
+                obs_nobg.inputs.wavelength.mean(obs.axis_time),
                 np.nanmedian(obs_nobg.outputs, axis=axis_txy),
                 label="corrected",
             )

pyproject.toml

@@ -16,7 +16,7 @@ classifiers = [
 dependencies = [
     "astropy",
     "requests",
-    "named-arrays==0.14.1",
+    "named-arrays==0.14.2",
 ]
 dynamic = ["version"]